In the technical field of data processing, “screening” is widely used as a basic means.
When using the screening function, in addition to screening data that meet specified conditions so as to view, process and analyze the data, sometimes users also require to learn and statistically compute the overall condition and constituent of the data.
Currently, a technical solution employed by a user to learn and statistically compute the overall condition and constituent of the data is: setting a group of filter conditions to check the number of records that meet the group of filter conditions and obtaining a count; and then changing the filter conditions, checking again and obtaining another count; and repeating in such a way for several times.
For example, as shown in FIG. 1, the data table in the figure is an employee comprehensive information statistical table for a certain company. When an administrator needs to know the number of employees in each department, the method the administrator employs is: summarizing types of the company's departments; performing screening and statistical operation on employees according to the different departments respectively. Specifically, the administrator needs to count the types of the company's departments, and then screen the employee information according to the department types one by one. First, the administrator sets a filter condition as “Department=Product department”; the data table receives the filter condition, statistically computes all the information of the product department of the company in the data table and counts the number of records and obtains a count, as shown in FIG. 2. The administrator then changes the filter condition as “Department=Development department”; the data table receives the filter condition, obtains all the information of the development department of the company in the data table and counts the number of records, thus obtaining another count. Similarly, the administrator changes the filter condition as “Department=Quality department”; the data table receives the filter condition, obtains all the information of the quality department of the company in the data table and counts the number of records, thus obtaining still another count. Obviously, when there are many department types or many filter conditions, such method is time-consuming and inefficient.